Methods for estimating adjusted risk ratios
Peter Cummings
Department of Epidemiology
School of Public Health
and
Harborview Injury Prevention and Research Center
University of Washington
Seattle, WA
[email protected]
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Abstract. The risk ratio can be a useful statistic for summarizing the results of
cross-sectional, cohort, and randomized trial studies. I discuss several methods for
estimating adjusted risk ratios and show how they can be executed in Stata, including
1) Mantel–Haenszel and inverse-variance stratified methods; 2) generalized
linear regression with a log link and binomial distribution; 3) generalized linear
regression with a log link, normal distribution, and robust variance estimator; 4)
Poisson regression with a robust variance estimator; 5) Cox proportional hazards
regression with a robust variance estimator; 6) standardized risk ratios from logistic,
probit, complementary log-log, and log-log regression; and 7) a substitution
method. Advantages and drawbacks are noted for some methods.
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Peter Cummings
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risk ratio, odds ratio
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